The current state of the art in online search engines is highly advanced in its ability to retrieve documents (e.g., web pages or portions thereof, images, etc.) that are responsive to the terms of a query. Search engines today can quickly retrieve specific documents that match the terms of the query. However, current search engines often return documents that while accurately correspond to the specific terms of the query, do not in any way reflect the user's underlying interests. Thus, two different users, one who is very interested in sports, and another who is interested in politics, will obtain exactly the same results to a given query, say “drug testing in baseball,” even though the first user may be more interested in learning about which teams have implemented drug testing, while the latter user is more interested in learning about legislation related to drug testing in sports. Thus, there is a need for providing a mechanism and methodology for personalizing search results in accordance with the interests of the users.
Further, while a user may have particular set of interests that may be useful in processing their search query, a user may not want to always have such interests influence the query results. Thus, it would be desirable to a provide a mechanism and a methodology by which the user can variably adjust the degree to which his interests influence the results of a given search query.